Deadline and budget-constrained archimedes optimization algorithm for workflow scheduling in cloud

Cloud computing has revolutionized various domains over the past decade, providing accessible computational and storage resources at reduced costs. The exponential growth in data volumes and processing complexity, particularly due to the proliferation of IoT devices and applications across fields su...

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Veröffentlicht in:	Cluster computing Jg. 28; H. 2; S. 117
Hauptverfasser:	Kushwaha, Shweta, Singh, Ravi Shankar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.04.2025 Springer Nature B.V
Schlagworte:	Algorithms Budgets Cloud computing Computer Communication Networks Computer Science Constraints Costs Deadlines Energy consumption Energy efficiency Heuristic Heuristic methods Multiple objective analysis Operating Systems Optimization Optimization algorithms Pareto optimum Problem solving Processor Architectures Resource scheduling Resource utilization Scheduling Task complexity Task scheduling Variance analysis Workflow Workloads Metaheuristics Deadline Optimization techniques Pareto-optimality Cost-efficiency Budget Archimedes optimization algorithm Workflow scheduling
ISSN:	1386-7857, 1573-7543
Online-Zugang:	Volltext
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